Compare · GPUs & AI chips
Blackwell B200 SXM vs H100 SXM
RANKED BY DENSE FP16/BF16 TENSOR TFLOPS PER CHIP
#3 VS #9
CHECKED 06 SEPT 2026
Side by side
Verdict
Blackwell B200 SXM ranks #3 of 20 on Dense FP16/BF16 tensor TFLOPS per chip (2.25 PFLOPS); H100 SXM ranks #9 (0.990 PFLOPS).
Rank 03 of 20 · leads
Dense FP16/BF16 tensor TFLOPS per chip
2.25 PFLOPS
MakerNVIDIA
Date2025
Verified04 Sept 2026
Evidence
NVIDIA HGX Platform page, HGX B200 row ("8x NVIDIA Blackwell SXM", footnote 4: "HGX B300 and HGX B200 shipping now"). FP16/BF16 Tensor Core is listed as 36 PFLOPS for the 8-GPU board. Footnote 2: dense is half the sparse spec. Dense board total is therefore 18 PFLOPS; per chip 18 / 8 = 2.25 PFLOPS. Total memory 1.4 TB => 180 GB HBM3E per SXM.Rank 09 of 20
Dense FP16/BF16 tensor TFLOPS per chip
0.990 PFLOPS
MakerNVIDIA
Date2022
Verified04 Sept 2026
Evidence
NVIDIA H100 product page, H100 SXM column: FP16/BF16 Tensor Core 1,979 teraFLOPS. H100 datasheet footnote 2: "With sparsity." Dense is 1,979 / 2 = 989.5 TFLOPS (0.990 PFLOPS). 80 GB HBM3. Tied with H200 SXM on this compute metric.Try another pair
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Source Vendor product pages and official spec documents (AMD Instinct MI355X / MI350X / MI325X / MI300X / MI300A / MI250X / MI250 / MI210; NVIDIA…
Last checked 06 Sept 2026